scholarly journals Intelligent Health Services Based on Biomedical Smart Sensors

2020 ◽  
Vol 10 (23) ◽  
pp. 8497
Author(s):  
Ricardo Colomo-Palacios ◽  
Juan A. Gómez-Pulido ◽  
Alfredo J. Pérez
Keyword(s):  
Internet Of Things ◽  
Health Services ◽  
Data Science ◽  
Disease Diagnosis ◽  
Research Articles ◽  
Smart Sensors ◽  
Special Issue ◽  
Human Welfare ◽  
Oriented Area ◽  
Advanced Technologies

Health services can be improved by means of intelligent techniques that handle efficiently massive volumes of data collected from biomedical variables. Nowadays, these services are not only oriented to disease diagnosis and prevention, but wellness too. Advanced technologies and last trends in computing, internet of things, sensors, and data science are driving the development of new systems and applications in the area of intelligent health services based on biomedical smart sensors that deserve to be known. Through five research articles and a review, this Special Issue provides the opportunity to obtain a representative view of the potential of these technologies when applied to such a human welfare-oriented area.

scholarly journals Introduction to the Special Issue: Applications of Internet of Things

Symmetry ◽  
2018 ◽  
Vol 10 (9) ◽  
pp. 374 ◽  
Author(s):  
Chi-Hua Chen ◽  
Eyhab Al-Masri ◽  
Feng-Jang Hwang ◽  
Despo Ktoridou ◽  
Kuen-Rong Lo
Keyword(s):  
Internet Of Things ◽  
Smart Home ◽  
Data Science ◽  
Cooperative Spectrum Sensing ◽  
Smart Homes ◽  
Recognition System ◽  
Special Issue ◽  
Smart Transportation ◽  
User Classification ◽  
Novel Approach

This editorial introduces the special issue, entitled “Applications of Internet of Things”, of Symmetry. The topics covered in this issue fall under four main parts: (I) communication techniques and applications, (II) data science techniques and applications, (III) smart transportation, and (IV) smart homes. Four papers on sensing techniques and applications are included as follows: (1) “Reliability of improved cooperative communication over wireless sensor networks”, by Chen et al.; (2) “User classification in crowdsourcing-based cooperative spectrum sensing”, by Zhai and Wang; (3) “IoT’s tiny steps towards 5G: Telco’s perspective”, by Cero et al.; and (4) “An Internet of things area coverage analyzer (ITHACA) for complex topographical scenarios”, by Parada et al. One paper on data science techniques and applications is as follows: “Internet of things: a scientometric review”, by Ruiz-Rosero et al. Two papers on smart transportation are as follows: (1) “An Internet of things approach for extracting featured data using an AIS database: an application based on the viewpoint of connected ships”, by He et al.; and (2) “The development of key technologies in applications of vessels connected to the Internet”, by Tian et al. Two papers on smart home are as follows: (1) “A novel approach based on time cluster for activity recognition of daily living in smart homes”, by Liu et al.; and (2) “IoT-based image recognition system for smart home-delivered meal services”, by Tseng et al.

scholarly journals Introduction to the Special Issue on Advanced Technologies in Assessment: A Science-Practice Concern

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Cornelius König ◽  
Andrew Demetriou ◽  
Philipp Glock ◽  
Annemarie Hiemstra ◽  
Dragos Iliescu ◽  
...  
Keyword(s):  
Psychological Assessment ◽  
Data Science ◽  
Interdisciplinary Collaboration ◽  
The European Union ◽  
Special Issue ◽  
Assessment Practice ◽  
Science Practice ◽  
Personnel Assessment ◽  
Advanced Technologies ◽  
Computer Scientists

This article is based on conversations from the project “Big Data in Psychological Assessment” (BDPA) funded by the European Union, which was initiated because of the advances in data science and artificial intelligence that offer tremendous opportunities for personnel assessment practice in handling and interpreting this kind of data. We argue that psychologists and computer scientists can benefit from interdisciplinary collaboration. This article aims to inform psychologists who are interested in working with computer scientists about the potentials of interdisciplinary collaboration, as well as the challenges such as differing terminologies, foci of interest, data quality standards, approaches to data analyses, and diverging publication practices. Finally, we provide recommendations preparing psychologists who want to engage in collaborations with computer scientists. We argue that psychologists should proactively approach computer scientists, learn computer scientific fundamentals, appreciate that research interests are likely to converge, and prepare novice psychologists for a data-oriented scientific future.

scholarly journals Noninvasive Early Disease Diagnosis by Electronic-Nose and Related VOC-Detection Devices

Biosensors ◽  
2020 ◽  
Vol 10 (7) ◽  
pp. 73 ◽  
Author(s):  
Alphus Dan Wilson
Keyword(s):  
Early Detection ◽  
Electronic Nose ◽  
Disease Diagnosis ◽  
Plant Diseases ◽  
Research Articles ◽  
Special Issue ◽  
Early Disease ◽  
Invasive Pests ◽  
Detection And Diagnosis ◽  
Voc Detection

This editorial provides an overview and summary of recent research articles published in Biosensors journal, volumes 9 (2019) and 10 (2020), within the Special Issue “Noninvasive Early Disease Diagnosis”, which focused on recent sensors, biosensors, and clinical instruments developed for the noninvasive early detection and diagnosis of human, animal, and plant diseases or invasive pests. The six research articles included in this Special Issue provide examples of some of the latest electronic-nose (e-nose) and related volatile organic compound (VOC)-detection technologies, which are being tested and developed to improve the effectiveness and efficiency of innovative diagnostic methodologies for the early detection of particular diseases and pest infestations in living hosts, prior to symptom development.

scholarly journals Recent Advances in Kinase Drug Discovery Part I: The Editors’ Take

2021 ◽  
Vol 22 (14) ◽  
pp. 7560
Author(s):  
Julie A. Tucker ◽  
Mathew P. Martin
Keyword(s):  
Drug Discovery ◽  
Research Articles ◽  
Special Issue ◽  
Recent Advances ◽  
Enzyme Family ◽  
Selection Of

This special issue on Advances in Kinase Drug Discovery provides a selection of research articles and topical reviews covering all aspects of drug discovery targeting the phosphotransferase enzyme family [...]

Editorial for Special Issue on Flexible Cloud and Edge for Internet‐of‐Things

2021 ◽  
Author(s):  
Deze Zeng ◽  
Ruidong Li ◽  
Zhi Zhou ◽  
Ruiting Zhou ◽  
Rami Langar ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Special Issue

Internet of things-based cloud computing platform for analyzing the physical health condition

2021 ◽  
pp. 1-15
Author(s):  
Mengyao Cui ◽  
Seung-Soo Baek ◽  
Rubén González Crespo ◽  
R. Premalatha
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Health Monitoring ◽  
Tracking System ◽  
Disease Diagnosis ◽  
Health Condition ◽  
Computing Platform ◽  
Concept Model ◽  
Patient Health ◽  
Cloud Servers

BACKGROUND: Health monitoring is important for early disease diagnosis and will reduce the discomfort and treatment expenses, which is very relevant in terms of prevention. The early diagnosis and treatment of multiple conditions will improve solutions to the patient’s healthcare radically. A concept model for the real-time patient tracking system is the primary goal of the method. The Internet of things (IoT) has made health systems accessible for programs based on the value of patient health. OBJECTIVE: In this paper, the IoT-based cloud computing for patient health monitoring framework (IoT-CCPHM), has been proposed for effective monitoring of the patients. METHOD: The emerging connected sensors and IoT devices monitor and test the cardiac speed, oxygen saturation percentage, body temperature, and patient’s eye movement. The collected data are used in the cloud database to evaluate the patient’s health, and the effects of all measures are stored. The IoT-CCPHM maintains that the medical record is processed in the cloud servers. RESULTS: The experimental results show that patient health monitoring is a reliable way to improve health effectively.

Sign in / Sign up

Export Citation Format

Share Document